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DBMS > Databricks vs. Fauna vs. Ingres

System Properties Comparison Databricks vs. Fauna vs. Ingres

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Well established RDBMS
Primary database modelDocument store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score86.46
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.43
Rank#148  Overall
#26  Document stores
#13  Graph DBMS
#68  Relational DBMS
#13  Time Series DBMS
Score3.47
Rank#79  Overall
#43  Relational DBMS
Websitewww.databricks.comfauna.comwww.actian.com/­databases/­ingres
Technical documentationdocs.databricks.comdocs.fauna.comdocs.actian.com/­ingres
DeveloperDatabricksFauna, Inc.Actian Corporation
Initial release201320141974 infooriginally developed at University Berkely in early 1970s
Current release12.0, July 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC
Server operating systemshostedhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP API.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesPython
R
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlIdentity management, authentication, and access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFauna infopreviously named FaunaDBIngres
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFauna infopreviously named FaunaDBIngres
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